LinkedIn Plots Career Success Paths

Deep Nishar spends his days poring over the terabytes of data amassed from the 75 million members of LinkedIn, the networking site. (One terabyte holds the text of a million books.) These days he is building "data maps" that help people identify the connections they have now and learn what they need to do to be in that ideal job--or on the right path to it.

If you aim to be a chief financial officer of a 5,000-person company, for example, the data show you need to get an M.B.A. within nine years of starting work. Graduate from college with a physics degree and there is a 22% chance you'll be a software engineer in two years. Join the military and your chances of being homeless someday go way up, since you lose your support network when you leave the service. Nishar is tackling this last problem by finding ways that army skills can turn into private-sector work.

Nishar, whose title is vice president of products and user experience, combs work histories that often go back decades and looks at the 2,500 new connections a minute formed among LinkedIn members. He gets insights into American economic history (job switching almost doubled between 1970 and 2000, to 3.1 jobs a decade), résumé tips ("proven track record" is an overused phrase) and thoughts on fate (chief executives tend to have short names--like Jack, Amir and Boris).

Nishar, 41, grew up in India and earned a master's in electrical engineering and a Harvard M.B.A. before joining search giant
Google
in 2003. There he won a "founder's award" for improving the advertising placement algorithm, then headed the products business in Asia. Today 100 data researchers among LinkedIn's 700 employees look at everything from data center behavior, search and mobile communications, as well as analysis of personal data. The researchers have experience in such fields as brain surgery, computer science, meteorology and poetry.

"They all love data," he says. "It's hard to synopsize a life or tell someone what they might do next with their skills, but looking at where people worked, who they know, what conferences they attend, can do that well." That is a big thing, says Nishar. "Machine-based systems like Google can't keep up with organizing all the data," he says. "Interesting and important problems will be solved by looking at social networks."

Just making common descriptions of how people characterize themselves is a challenge: LinkedIn has seen 6,000 variants of the job "software engineer" described in English and 8,000 different ways people say they worked at IBM, including hundreds of company locations, nicknames of divisions, variations on job titles, even some misspellings.

"If we get it right," says Nishar, "we can find ways that everybody can add to their skills."